On the Path to 2X Learning: Exploring the Possibilities of Advanced Speech Recognition

On the Path to 2X Learning: Exploring the Possibilities of Advanced Speech Recognition

One of the most advanced technologies brought to bear on language learning is automatic speech recognition (ASR). It is proposed that ASR-enhanced materials for self-study can effectively increase the student's learning twofold over conventional self-study materials. Past and current efforts at...

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Bibliographic Details
Published in:CALICO journal Vol. 16; no. 3; pp. 295 - 310
Main Authors: LaRocca, COL Stephen A., Morgan, John J., Bellinger, Sherri M.
Format: Journal Article
Language:English
Published: San Marcos CALICO Journal 1999
Equinox Publishing Ltd
Subjects:
Authoring
Authoring Aids (Programming)
Automatic Speech Recognition
Bears
Calico
Computer Assisted Instruction
Computers in education
Courseware
Developers
Educational Environment
Grammar Translation Method
Independent Study
Instructional Materials
Language acquisition
Language Proficiency
Language Skills
Learning
Learning Processes
Military
Military technology
Multimedia Materials
Nonnative languages
Overviews: Technologies, Projects, Products
Programmers
Second Language Instruction
Second language learning
Self study
Speech recognition
Teaching Methods
Vocabulary
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Summary:One of the most advanced technologies brought to bear on language learning is automatic speech recognition (ASR). It is proposed that ASR-enhanced materials for self-study can effectively increase the student's learning twofold over conventional self-study materials. Past and current efforts at the U.S. Military Academy are described, aimed at integrating advanced ASR into courseware authoring systems. Practical, technical, and pedagogical issues confronting both programmers and courseware developers are discussed. Possible directions for this emerging technology are forwarded based on past research, current experimental evidence, and the future of language learning in an era of technology.
Bibliography:ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 23
ISSN:0742-7778
2056-9017
2056-9017
DOI:10.1558/cj.v16i3.295-310